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Photonic computing and neuromorphic computing are attracting tremendous interests in breaking the memory wall of traditional von Neumann architecture. Photonic memristors equipped with light sensing, data storage, and in...

This article explores the integration of project-based learning with insights from ornithological observation to foster clinical intuition in medical education, especially in dermatology. By adapting teaching strategies ...

Chip-scale integrated optical signal processors promise to support a multitude of signal processing functions with bandwidths beyond the limit of microelectronics. Previous research has made great contributions in terms ...

ABSTRACT Background and Aims Human metapneumovirus (hMPV) is a leading cause of acute respiratory tract infections, particularly in children, older adults, and individuals with immunocompromising conditions. Despite incr...

One of the most evident costs in cow farming is the identification of the animals. Classic identification processes are labour-intensive, prone to human errors and invasive for the animal. An automated alternative is an ...

The recognition of areas of endemism (AEs) is important for conservation biology and biogeographical regionalization. Our objective was to quantitatively identify AEs and distributional congruence patterns of native rode...

BackgroundFibrinous bronchitis, also known as plastic bronchitis, is a rare airway disorder characterized by branching bronchial casts that replicate the architecture of the bronchial tree. Adult cases are uncommon and f...

Partially clonal plants are common and often act as ecological foundation species. Patterns of clonal genotypes (genets) and their vegetative modules (ramets) in natural populations remain poorly documented. Knowledge ga...

Abstract Background Mental health workers (MHWs) face ongoing challenges, including heavy workloads, staff shortages, and pressure due to long patient waiting lists. These factors contribute to high levels of stress, aff...

Automatic valet parking using learning function is proposed in this study. The number plate (vehicle registration plate or license plate) of each vehicle is read using a camera when entering and leaving the parking lot. ...

Abstract Background Machine learning methods are widely used to detect behavioural data patterns. Although these new mathematical methods are useful tools, the interpretation of the results are often ambivalent unless ...

This study explores the phonetics and phonology of regional accents in English, aiming on how distinctions in pronunciation impact intelligibility, identity, and linguistic acuity. English, as a global language, displays...

We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression. Taking a pattern classification approach, we consider each pixel in an image as a coordinate in...

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning alg...

The recognition of handwritten numerals has many important applications, such as automatic lecture of zip codes in post offices, and automatic lecture of numbers in checknotes. In this paper we present a preprocessing me...

The ability of learning networks to generalize can be greatly enhanced by providing constraints from the task domain. This paper demonstrates how such constraints can be integrated into a backpropagation network through ...

Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models (GMMs) to determine how well each state of each HMM fits a frame or a sh...

Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers...

We have developed a near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. The computational appro...

Despite significant recent advances in the field of face recognition [10, 14, 15, 17], implementing face verification and recognition efficiently at scale presents serious challenges to current approaches. In this paper ...

Presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prot...

An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and a...

We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among...

Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrar...