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Found 7 papers, 2 papers with code
A Comprehensive Overview of Large Language Models
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond.
Detecting Severity of Diabetic Retinopathy from Fundus Images using Ensembled Transformers
Diabetic Retinopathy (DR) is considered one of the primary concerns due to its effect on vision loss among most people with diabetes globally.
Deep Analysis of Visual Product Reviews
In the past, the researchers worked on analyzing language feedback, but here we do not take any assistance from linguistic reviews that may be absent, since a recent trend can be observed where customers prefer to quickly upload the visual feedback instead of typing language feedback.
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.
Recognizing Facial Expressions in the Wild using Multi-Architectural Representations based Ensemble Learning with Distillation
We proposed two models, EmoXNet which is an ensemble learning technique for learning convoluted facial representations, and EmoXNetLite which is a distillation technique that is useful for transferring the knowledge from our ensemble model to an efficient deep neural network using label-smoothen soft labels for able to effectively detect expressions in real-time.
A Survey on Image Aesthetic Assessment
Automatic image aesthetics assessment is a computer vision problem dealing with categorizing images into different aesthetic levels.
Towards a Dedicated Computer Vision Tool set for Crowd Simulation Models
Understanding underlying dynamics and behavior of crowd is becoming areas of interest for most of computer scientists.
