Early diagnosis of Alzheimer's disease and its prodromal stage, also known as mild cognitive impairment (MCI), is critical since some patients with progressive MCI will develop the disease. We propose a multi-stream deep convolutional neural network fed patch-based imaging data to classify stable MCI. First, we compare MRI images cognitively normal subjects identify distinct anatomical landmarks using multivariate statistical test. These are then used extract patches that into proposed...

Glaucoma, a leading cause of irreversible blindness worldwide, poses significant diagnostic challenges due to its reliance on subjective evaluation. Recent advances in computer vision and deep learning have demonstrated the potential for automated assessment. This paper provides comprehensive survey studies AI-based glaucoma diagnosis using fundus, optical coherence tomography, visual field images, with focus learning-based methods. We searched Web Science, PubMed, IEEE Xplore, Google...

Spiking neural networks (SNNs) present the potential for ultra-low-power computation, especially when implemented on dedicated neuromorphic hardware. However, a significant challenge is efficient conversion of continuous real-world data into discrete spike trains required by SNNs. In this paper, we introduce Learning Adaptive Spike Thresholds (LAST), novel, trainable encoding strategy designed to address challenge. The LAST encoder learns adaptive thresholds transform signals varying...

Oyster fungi Pleurotus djamor generate actin potential like spikes of electrical potential. The trains might manifest propagation growing mycelium in a substrate, transportation nutrients and metabolites communication processes the network. spiking activity networks is highly variable compared to neural therefore can not be analysed by standard tools from neuroscience. We propose original techniques for detecting classifying fungi. Using these techniques, we analyse information-theoretic...

Face recognition has been a long standing problem in computer vision. Histograms of Oriented Gradients (HOGs) and Local Binary Patterns (LBPs) have proven to be an effective descriptor for object general face particular. In this paper, we investigate simple but powerful approach make robust use HOG LBP features recognition. The three main contributions work are: First, order compensate errors facial feature detection due occlusions, pose illumination changes, propose extract descriptors from...

This paper introduces a database of over 3,600 color images which we collected from 616 different human faces. It includes facial people between ages 2–85. Face persons with is needed to generate reliable age classification algorithm. Four poses, two expressions, and one image glasses were taken if the subjects interested. Information such as career, kind skin, fingerprint, cosmetic points (surgical points, fracture or laceration on face) participants. The background was white frame only...

Monitoring the spread of disease-carrying mosquitoes is a first and necessary step to control severe diseases such as dengue, chikungunya, Zika or yellow fever. Previous citizen science projects have been able obtain large image datasets with linked geo-tracking information. As number international collaborators grows, manual annotation by expert entomologists amount data gathered these users becomes too time demanding unscalable, posing strong need for automated classification mosquito...

There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy proposed biometric data analysis methods. For instance, people with chronic pain (CP) unconsciously adapt specific movements protect themselves from injury or additional pain. Because there no dedicated benchmark database analyse this correlation, we considered one circumstances that potentially influence person's during daily...

Kombucha is a type of tea that fermented using yeast and bacteria. During this process, film made cellulose produced. This has unique properties such as biodegradability, flexibility, shape conformability, ability to self-grow well be produced across customized scales. In our previous studies, we demonstrated mats exhibit electrical activity represented by spikes the potential. We propose microbial fermentation method for in situ functionalization modulate electroactive nature mats, where...

Des pite the success of License Plate Recognition (LPR) methods in past decades, this problem is quite a challenge due to diversity plate formats and multiform outdoor illumination conditions during image acquisition. This paper presents real-time robust method for Persian license location recognition. The proposed consists four main steps namely (I) localization (II) Normalization, (III) Character segmentation, (IV) Optical character First, all plates grabbed are located rapidly accurately...

Fungi cells can sense extracellular signals via reception, transduction, and response mechanisms, allowing them to communicate with their host adapt environment. They feature effective regulatory protein expressions that enhance regulate adaptation various triggers such as stress, hormones, physical stimuli light, factors. In our recent studies, we have shown Pleurotus oyster fungi generate electrical potential impulses in the form of spike events exposure environmental, mechanical, chemical...

Complementary medicine emphasizes therapies which are claimed to improve quality of life, prevent disease, and address conditions that conventional has limited success in curing. Iridology is an alternative technique examines patterns, colors, other characteristics the iris determine information about a patient's systemic health. The objective this paper validate use iridology find out body's organs abnormalities. proposed method consists (i) finding center its radius, (ii) mapping chart...

Malware is defined as any type of malicious code that the potent to harm a computer or network. Modern malwares are accompanied with mutation characteristics, namely polymorphism and metamorphism. They let generate enormous number variants. Rising metamorphic entails hardship in analyzing them for signature extraction database updates. In spite broad use signature-based methods security products, they not able detect new unseen morphs malware, it stemmed from changing structure malware well...

Glaucoma, a leading cause of irreversible blindness, necessitates early detection for accurate and timely intervention to prevent vision loss. In this study, we present novel deep learning framework that leverages the diagnostic value 3D Optical Coherence Tomography (OCT) imaging automated glaucoma detection. framework, integrate pre-trained Vision Transformer on retinal data rich slice-wise feature extraction bidirectional Gated Recurrent Unit capturing inter-slice spatial dependencies....

Immunocytochemistry (ICC) is a microscopic imaging technique that used to assess the presence of specific antigen in cells utilizing antibody for allowing visualization and examination processes. Number an ICC image considered as one most important indicators process. In this paper, analysis approach proposed order count number images. For purpose, morphological filtering done clean up noise. Then, nucleuses antibodies are separated by classifying relevant colors using Nearest Neighbor...