Academic Articles & Research Papers

Data-Efficient Transformer Model for Retinal Artery-Vein Segmentation in Landmark-Deficient OCT Angiography.

FieldMaizeLeaf-8: A real-field early vegetative maize leaf stress image dataset from Bangladesh.

Inverse Evolution Layers: Physics-informed Regularizers for Image Segmentation.

MoringaLeafNet: A multi-class leaf disease dataset for precision agriculture and deep learning researchMendeley Data

Moringa Oleifera, which has outstanding nutritional and health benefits, is prized around the world because its leaves are rich in essential vitamins, antioxidants, and minerals that support digestion, help the immune system, and fight infl...

Learning Feature Fusion in Deep Learning-Based Object Detector

Object detection in real images is a challenging problem in computer vision. Despite several advancements in detection and recognition techniques, robust and accurate localization of interesting objects in images from real-life scenarios re...

Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection

The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environmen...

Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials

Topological defects play a key role in the structures and dynamics of liquid crystals and other ordered systems. There is a recent interest in studying defects in different biological systems with distinct textures. However, a robust method...

Deeply Exploiting Long-Term View Dependency for 3D Shape Recognition

Recognition of 3D shapes is a fundamental task in computer vision. In recent years, view-based deep learning has emerged as an effective approach for 3D shape recognition. Most existing view-based methods treat the views of an object as an ...

Overcomplete graph convolutional denoising autoencoder for noisy skeleton action recognition

Abstract Current skeleton‐based action recognition methods usually assume the input skeleton is complete and noise‐free. However, it is inevitable that the captured skeletons are incomplete due to occlusions or noisy due to changes in the e...

Hybrid Deep Learning Algorithms for Dog Breed Identification—A Comparative Analysis

Deep learning and computer vision algorithms will be applied to find the breed of the dog from an image. The goal is to have the user submit an image of a dog, and the model will choose one of the 120 breeds stated in the dataset to determi...

A Comparative Study of Physically Accurate Synthetic Shadow Datasets in Agricultural Settings with Human Activity

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotat...

Parallax attention stereo matching network based on the improved group-wise correlation stereo network

Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep...

Automated diabetic retinopathy grading and lesion detection based on the modified R‐FCN object‐detection algorithm

In this work, we develop a computer‐aided retinal image screening system that can perform automated diabetic retinopathy (DR) grading and DR lesion detection in retinal fundus images. We propose a modified object‐detection method for this t...

Computer Vision

Computer vision is a field of study that enables computers to interpret and understand visual data from the world around us. This field has seen significant advancements in recent years, thanks to the increasing availability of large datase...

Pharmacotherapy augmentation strategies in treatment-resistant anxiety disorders.

Part‐level attention networks for cross‐domain person re‐identification

Abstract Person re‐identification (Re‐ID) is in significant demand for intelligent security and single or multiple‐target tracking. However, there are issues in the person Re‐ID tasks, such as sharp decline in cross‐data sets detection accu...

Efficient One-Dimensional Network Design Method for Underwater Acoustic Target Recognition

Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets. However, tr...

Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

Generalizable stereo depth estimation with masked image modelling

Abstract Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizab...

Enhanced Skin Condition Prediction Through Machine Learning Using Dynamic Training and Testing Augmentation

In recent years, deep learning has taken the spotlight in automated medical bioimaging. However, the performance of current state-of-the-art score stems primarily from well-tuned parameters and architecture. There is still only limited rese...