Academic Articles & Research Papers

Real Time Eye Detector with Cascaded Convolutional Neural Networks

An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extr...

A Complete System for Automated Semantic–Geometric Mapping of Corrosion in Industrial Environments

Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. Traditional tech...

Sequential Normalization: Embracing Smaller Sample Sizes for Normalization

Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...

TRAMON: An automated traffic monitoring system for high density, mixed and lane-free traffic

This paper introduces a new visual dataset and framework to facilitate computer-vision-based traffic monitoring in high density, mixed and lane-free traffic (TRAMON). While there are advanced deep learning algorithms that can detect and tra...

Implementation and Design of a Smart Pharmacy Automation System Using Raspberry Pi

Manual medication dispensing in pharmacies remains prone to human errors and is time-intensive, particularly under high patient loads, while existing commercial automation solutions are cost-prohibitive for small to medium-sized pharmacy se...

TSER: A Two-Stage Character Segmentation Network With Two-Stream Attention and Edge Refinement

Segmenting characters in an image is a classic yet challenging task in computer vision. Correctly determining boundaries of adhesive characters with various scales and shapes is essential for character segmentation, especially for separatin...

Soft–Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal

Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...

A human activity recognition method based on Vision Transformer

Abstract Human activity recognition has a wide range of applications in various fields, such as video surveillance, virtual reality and human–computer intelligent interaction. It has emerged as a significant research area in computer vision...

An accurate, efficient, and accessible AI-powered solution for wildlife re-identification in conservation

Abstract Accurate wildlife re-identification is critical for a wide range of ecological studies, including density estimation via capture–recapture, demographic analyses, and behavioral research. We pr esent GIRAFFE (Generalized Image-based...

Discriminant Affinity Matrix for Deterministic Motion Trajectory Segmentation

We present a novel algorithm (DAM) for deterministic motion trajectory segmentation by using epipolar geometry and adaptive kernel-scale voting. DAM is based on geometric models and exploits the information derived from superpixels to deter...

Review of Weed Detection Methods Based on Computer Vision

Weeds are one of the most important factors affecting agricultural production. The waste and pollution of farmland ecological environment caused by full-coverage chemical herbicide spraying are becoming increasingly evident. With the contin...

A survey of public datasets for computer vision tasks in precision agriculture

Computer vision technologies have attracted significant interest in precision agriculture in recent years. At the core of robotics and artificial intelligence, computer vision enables various tasks from planting to harvesting in the crop pr...

Mammography datasets and artificial intelligence for breast cancer detection: challenges, bias, and future directions.

Multistage Convolutional Neural Network With Deformable Attention for Word-Level Offline Text-Independent Writer Identification

Offline writer identification is an essential component of biometric and forensic security fields, focusing on identifying the authors of handwritten documents in physical form. Historically, this approach has focused on text-dependent iden...

The Intelligent Ecosystem: How we are Architecting the Future of Environmental Services with AI

As the global economy confronts the dual imperatives of ecological preservation and technological advancement, we at Veolia, are executing a comprehensive strategy that places Artificial Intelligence (AI) at the core of our operations and f...

Learning by Watching: A Review of Video-Based Learning Approaches for Robot Manipulation

Robot learning of manipulation skills is hindered by the scarcity of diverse, unbiased datasets. While curated datasets can help, challenges remain regarding generalizability and real-world transfer. Meanwhile, large-scale ‘in-the-wi...

SAIN:structure-aware image inpainting for large missing areas

Abstract Image inpainting is crucial for restoring missing or corrupted regions in images, with diverse applications in computer vision and digital content creation. Existing deep learning-based methods, however, often struggle with large o...

Deep-Learning based Melanoma Detection using Cloud Approach

The aim of computer vision techniquesand deep learning in the era of digitalization is to derive valuable insights from them and generate novel understanding. This makes it possible to employ imaging to quickly diagnose and treat a variety ...

A lightweight optimization framework for real-time pedestrian detection in dense and occluded scenes

Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...

An Improved Dense CNN Architecture for Deepfake Image Detection

Recent advancements in computer vision processing need potent tools to create realistic deepfakes. A generative adversarial network (GAN) can fake the captured media streams, such as images, audio, and video, and make them visually fit othe...