In the last few months, novel COVID19 pandemic has spread all over world. Due to its easy transmission, developing techniques accurately and easily identify presence of distinguish it from other forms flu pneumonia is crucial. Recent research shown that chest Xrays patients suffering depicts certain abnormalities in radiography. However, those approaches are closed source not made available community for re-producibility gaining deeper insight. The goal this work build open access datasets...

AI-based smart thermal perception systems can cater to the limitations of conventional imaging sensors by providing a more reliable data source in low-lighting conditions and adverse weather conditions. This research evaluates modifies state-of-the-art object detection classifier framework for vision with seven key classes order provide superior sensing scene understanding input advanced driver-assistance (ADAS). The networks are trained on public datasets is validated test three different...

Technology aided platforms provide reliable tools in almost every field these days. These being supported by computational power are significant for applications that need sensitive and precise data analysis. One such important application the medical is Automatic Lesion Detection System (ALDS) skin cancer classification. Computer diagnosis helps physicians dermatologists to obtain a second opinion proper analysis treatment of cancer. Precise segmentation cancerous mole along with...

Human thermography is considered to be an integral medical diagnostic tool for detecting heat patterns and measuring quantitative temperature data of the human body. It can used in conjunction with other procedures getting comprehensive medication results. In proposed study we have highlighted significance Infrared Thermography (IRT) role machine learning thermal image analysis health monitoring various disease diagnosis preliminary stages. The first part provides information about...

This study is focused on evaluating the real-time performance of thermal object detection for smart and safe vehicular systems by deploying trained networks GPU & single-board EDGE-GPU computing platforms onboard automotive sensor suite testing. A novel large-scale dataset comprising > 35,000 distinct frames acquired, processed, open-sourced in challenging weather environmental scenarios. The a recorded from lost-cost yet effective uncooled LWIR camera, mounted stand-alone an electric...

This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing robustness machine learning model training. Synthetic plays pivotal role in mitigating challenges associated with limited labeled datasets, thereby facilitating more effective training and fine-tuning. In this context, we aim to incorporate enhanced transformation techniques by extending recent success few-shot text-to-image latent models. The optimally...

Driver Monitoring Systems (DMS) represent a promising approach for enhancing driver safety within vehicular technologies. This research explores the integration of neuromorphic event camera technology into DMS, offering faster and more localized detection changes due to motion or lighting in an imaged scene. When applied observation human subject provides new level sensing capabilities over conventional imaging systems. The study focuses on application DMS by incorporating cameras, augmented...

Aconitase, the second enzyme of tricarboxylic acid cycle encoded by ACO1 in budding yeast Saccharomyces cerevisiae , catalyzes conversion citrate to isocitrate. aco1 Δ results mitochondrial DNA (mtDNA) instability. It has been proposed that Aco1 binds mtDNA and mediates its maintenance. Here we propose an alternative mechanism account for loss mutant cells. We found activated RTG pathway, resulting increased expression genes encoding synthase. By deleting RTG1 RTG3 or synthase, instability...

Smart parking systems having efficient vacant spot detection and vehicle entrance exit count can be quite beneficial for managing traffic it play a vital role reducing cost of fuel. Parking using visual streams from cameras as does not require any sensor to installed on location separately. In this paper, we proposed unique vacancy slot state-of-the-art vehicles based Faster R-CNN. Furthermore, is also determined deep convolution features. The system evaluated publically available PKLot...

In this research work, we proposed a novel ChildGAN, pair of GAN networks for generating synthetic boys and girls facial data derived from StyleGAN2. ChildGAN is built by performing smooth domain transfer using learning. It provides photo-realistic, high-quality samples. A large-scale dataset rendered with variety smart transformations: expressions, age progression, eye blink effects, head pose, skin hair color variations, variable lighting conditions. The comprises more than 300k distinct...

Gender classification has found many useful applications in the broader domain of computer vision systems including in-cabin driver monitoring systems, human–computer interaction, video surveillance crowd monitoring, data collection for retail sector, and psychological analysis. In previous studies, researchers have established a gender system using visible spectrum images human face. However, there are factors affecting performance these illumination conditions, shadow, occlusions, time...

Neuromorphic vision or event is an advanced technology, where in contrast to visible camera sensors that output pixels, the generates neuromorphic events every time there's a brightness change which exceeds specific threshold field of view (FoV). This study focuses on leveraging data for roadside object detection. proof concept towards building artificial intelligence (AI) based imaging pipelines can be used forward perception systems vehicular applications. The focus efficient stateof-...

The digitalisation of visual tasks through imaging techniques and Computer Vision has the potential disrupting manner in which Advanced Manufacturing processes are deployed. In this work we have collaborated with manufacturing industry to investigate effective usage end-to-end convolution neural networks (CNNs) enable advanced by inspecting seal integrity sterile barrier packaging highly regulated products, such as Medical Devices. For purpose, a novel 'DS1' dataset labelled images...

Event cameras provide a novel imaging technology for high-speed analysis of localized facial motions such as eye gaze, eye-blink and micro-expressions by taking input at the level an individual pixel. Due to this capability, lightweight amount output data these are being evaluated viable option driver monitoring systems (DMS). This research investigates impact pixel-bias alteration on DMS features, which are: face tracking, blink counting, head pose gaze estimation. In order do this, new...

This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing robustness machine learning model training. Synthetic generation plays pivotal role in mitigating challenges associated with limited labeled datasets, thereby facilitating more effective In this context, we aim to incorporate enhanced transformation techniques by extending recent success few-shot and small amount representation text-to-image latent models....

Stable Diffusion (SD) has gained a lot of attention in recent years the field Generative AI thus helping synthesizing medical imaging data with distinct features. The aim is to contribute ongoing effort focused on overcoming limitations scarcity and improving capabilities ML algorithms for cardiovascular image processing. Therefore, this study, possibility generating synthetic cardiac CTA images was explored by fine-tuning stable diffusion models based user defined text prompts, using only...

This paper presents a hand-written character recognition comparison and performance evaluation for robust precise classification of different characters. The system utilizes advanced multilayer deep neural network by collecting features from raw pixel values. hidden layers stack hierarchies non-linear since learning complex conventional networks is very challenging. Two state the art architectures were used which includes Caffe AlexNet [5] GoogleNet models [6] in NVIDIA DIGITS [10]....

Technology-assisted platforms provide reliable solutions in almost every field these days. One such important application the medical is skin cancer classification preliminary stages that need sensitive and precise data analysis. For proposed study Kaggle dataset utilized. The consists of two main phases. In first phase, images are preprocessed to remove clutters thus producing a refined version training images. To achieve that, sharpening filter applied followed by hair removal algorithm....

Due to the real-time acquisition and reasonable cost of consumer cameras, monocular depth maps have been employed in a variety visual applications. Regarding ongoing research estimation, they continue suffer from low accuracy enormous sensor noise. To improve prediction maps, this paper proposed lightweight neural facial estimation model based on single image frames. Following basic encoder-decoder network design, features are extracted by initializing encoder with high-performance...

Automatically segmenting groups and individuals from crowd images can be important for surveillance purpose. In this paper, we present a simplified detection segmentation system. Crowd scene divided into different regions: group, individual, row. Mask R-CNN with modified backbone architecture is employed image segmentation. The proposed system tested on BIWI dataset self-generated to achieve accuracy of 83%. Furthermore, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...