Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. Object detection is a key field in artificial intelligence, allowing computer systems to “see” their environments by detecting objects in visual images or videos.

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Viso.ai

OCTOBER 15, 2024

YOLO (You Only Look Once) is a state-of-the-art (SOTA) object-detection algorithm introduced as a research paper by J. About us : Viso Suite is an End-to-End Computer Vision Infrastructure that provides all the tools required to train, build, deploy, and manage computer vision applications at scale. Redmon, et al.

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Unite.AI

JULY 12, 2024

Acquired by Google in 2018, Socratic has become a go-to study companion for students looking for quick, reliable answers and in-depth explanations across a wide range of subjects, including math, science, literature, and social studies. Developed by Israeli startup EqsQuest Ltd.

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Flipboard

JULY 10, 2023

By using our mathematical notation, the entire training process of the autoencoder can be written as follows: Figure 2 demonstrates the basic architecture of an autoencoder: Figure 2: Architecture of Autoencoder (inspired by Hubens, “Deep Inside: Autoencoders,” Towards Data Science , 2018 ). Or requires a degree in computer science?

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Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al.,

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Viso.ai

OCTOBER 25, 2023

million seed round led by Accel to bring computer vision capabilities to companies across the globe! The investment will be used to further accelerate growing the team to serve customers worldwide, and to continue enhancing the computer vision platform’s end-to-end and no-code capabilities.

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PyImageSearch

NOVEMBER 13, 2023

One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,

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Towards AI

JULY 23, 2023

Year and work published Generative Pre-trained Transformer (GPT) In 2018, OpenAI introduced GPT, which has shown, with the implementation of pre-training, transfer learning, and proper fine-tuning, transformers can achieve state-of-the-art performance. So, the authors have used a two-stage process, following what we do as humans.

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Towards AI

DECEMBER 28, 2023

Black box algorithms such as xgboost emerged as the preferred solution for a majority of classification and regression problems. Later, Python gained momentum and surpassed all programming languages, including Java, in popularity around 2018–19. In 2023, we witnessed the substantial transformation of AI, marking it as the ‘year of AI.’

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Unite.AI

AUGUST 3, 2023

Our generative AI solution employs proprietary algorithms and machine learning techniques to streamline the creation of video-based standard operating procedures (SOPs), optimize workflows, and facilitate quick, efficient access to information via AI-driven chat features. Are there other types of machine learning algorithms that are used?

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Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions. YOLOv2 achieved 76.8 mAP at 67 FPS on the VOC 2007 dataset. at 22 milliseconds.

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IBM Journey to AI blog

AUGUST 1, 2023

Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data. An open-source model, Google created BERT in 2018. A foundation model is built on a neural network model architecture to process information much like the human brain does.

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Viso.ai

JUNE 12, 2024

provides a robust end-to-end computer vision infrastructure – Viso Suite. Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. About us : Viso.ai Get a demo here. without supervised pre-training.

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Viso.ai

JULY 9, 2024

Object detection is one of the crucial tasks in Computer Vision (CV). Computer vision researchers introduced YOLO architecture (You Only Look Once) as an object-detection algorithm in 2015. About Us: At Viso.ai, we power Viso Suite, the most complete end-to-end computer vision platform.

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Viso.ai

DECEMBER 18, 2023

YOLOv8 is the newest model in the YOLO algorithm series – the most well-known family of object detection and classification models in the Computer Vision (CV) field. offers the world’s leading end-to-end no-code Computer Vision Platform Viso Suite. Get a demo. The family YOLO model is continuously evolving.

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Towards AI

FEBRUARY 10, 2023

The term “artificial intelligence” may evoke the ideas of algorithms and data, but it is powered by the rare earth’s minerals and resources that make up the computing components [1]. The Myth of Clean Tech: Cloud Data Centers The data center has been a critical component of improvements in computing.

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Marktechpost

JULY 17, 2023

Synthetic data is generated algorithmically and used to train machine learning models, validate mathematical models, and act as a stand-in for test production or operational data test datasets. List of synthetic data startups and companies Datagen Israeli firm Datagen was founded in 2018 and has funded $22 million, including an $18.5

Machine Learning 52

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PyImageSearch

JULY 3, 2023

Figure 1: Netflix Recommendation System (source: “Netflix Film Recommendation Algorithm,” Pinterest ). Netflix recommendations are not just one algorithm but a collection of various state-of-the-art algorithms that serve different purposes to create the complete Netflix experience. Each row has a title (e.g.,

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Mlearning.ai

FEBRUARY 10, 2023

Techniques for reducing avoidable bias If you train your machine learning model and you see that your algorithm is suffering from high avoidable bias, you could the following techniques to reduce it. About Me: I am a Masters student in robotics, and my research interest is computer vision and deep learning. References [1].Ng,

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. ViT models outperform the current state-of-the-art (CNN) by almost x4 in terms of computational efficiency and accuracy.

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Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

JULY 17, 2024

Background and History of Neural Style Transfer NST is an example of an image styling problem that has been in development for decades, with image analogies and texture synthesis algorithms paving foundational work for NST. 2018) StarGAN extends GANs to multi-domain image translation. Here is the journey of NST. Gatys et al.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. Each season consists of around 17,000 plays. probability.

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Mlearning.ai

JULY 31, 2023

Traditionally, Computer Vision tasks use several Convolutional layers to extract significant features by iterating over the image using a fixed-sized box (kernel). One example is the Pairwise Inner Product (PIP) loss, a metric designed to measure the dissimilarity between embeddings using their unitary invariance (Yin and Shen, 2018).

Deep Learning 52

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Viso.ai

APRIL 18, 2024

Image segmentation task is a fundamental computer vision task that aims to partition a digital image into multiple segments or sets of pixels. The term “panoptic” originates from two Greek words “pan” (all) and “optic” (vision). distinguishing between multiple cars in an image).

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AWS Machine Learning Blog

MAY 2, 2023

There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19). If you have a large dataset, the SageMaker KNN algorithm may provide you with an effective semantic search.

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. Let’s get started!

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Heartbeat

JANUARY 29, 2024

At its core, Meta-Learning equips algorithms with the aptitude to quickly grasp new tasks and domains based on past experiences, paving the way for unparalleled problem-solving skills and generalization abilities. MAML trains a model's initial parameters to fine-tune rapidly for new tasks with just a few examples.

Machine Learning 52

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Sebastian Ruder

JANUARY 19, 2021

2018 ; Howard et al., More recently, contrastive learning gained popularity in self-supervised representation learning in computer vision and speech ( van den Oord, 2018 ; Hénaff et al., 2018 ) during dataset creation to filter out examples that are predicted correctly by current models. 2020 ; Le Bras et al.,

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Heartbeat

DECEMBER 8, 2023

This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms. is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets.

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The Stanford AI Lab Blog

JANUARY 21, 2022

Indeed, this recipe of massive, diverse datasets combined with scalable offline learning algorithms (e.g. self-supervised or cheaply supervised learning) has been the backbone of the many recent successes of foundation models 3 in NLP 4 5 6 7 8 9 and vision 10 11 12. Florence: A New Foundation Model for Computer Vision.

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AWS Machine Learning Blog

MAY 5, 2023

Voxel51 is the company behind FiftyOne, the open-source toolkit for building high-quality datasets and computer vision models. FiftyOne by Voxel51 is an open-source toolkit for curating, visualizing, and evaluating computer vision datasets so that you can train and analyze better models by accelerating your use cases.

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AWS Machine Learning Blog

AUGUST 16, 2023

Our solution is based on the DINO algorithm and uses the SageMaker distributed data parallel library (SMDDP) to split the data over multiple GPU instances. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. tif" --include "_B03.tif" tif" --include "_B04.tif"

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Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. In retrospect, this algorithm seems obvious, and perhaps it was. We were definitely in a Kuhnian pre-paradigmatic period. It would not be the last time that happened.)

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Mlearning.ai

MARCH 2, 2023

These publications either present small improvements of BERT, such as ALBERT and RoBERTa, or apply the principles behind BERT in other application areas, such as BEiT and ClipBERT in computer vision. In addition, it is known that Google has integrated BERT into its search algorithm to better understand search queries [17].

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). The same MLP is again used to calculate these probabilities[ 87 ].

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Google Research AI blog

FEBRUARY 28, 2023

For example, supporting equitable student persistence in computing research through our Computer Science Research Mentorship Program , where Googlers have mentored over one thousand students since 2018 — 86% of whom identify as part of a historically marginalized group.

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Snorkel AI

MARCH 1, 2023

It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write. 2018) This paper introduced BERT, a language model that uses bidirectional context to better understand the meaning of words in a sentence. The interface recommended two such bikes based on their small size.

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