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Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, improve on the previous best result in semant...

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic segme...

The six upper front teeth determine the appearance of Aesthetic dentistry. The study will define lateral incisors based on their lower angles as round, square, or square/round. LORIN molds to shape teeth were utilized. I...

Abstract As an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of t...

Recently, character recognition and deep learning have caught the attention of many researchers. Optical Character Recognition (OCR) usually takes an image of the character as input and generates the identical character ...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi model Convolutional Neural Network (CNN) dalam identifikasi tanda tangan. Metode CNN dipilih karena kemampuannya dalam mengekstraksi dan menganalisis fitur-fi...

Conventional Garden classification of femoral-neck fractures relies on radiography or CT, but image quality variations, indistinct fracture lines, and inter-observer differences often cause misclassification—especially...

With the proposal of the national dual-carbon strategic goal, distributed photovoltaic (PV) ushers in new development opportunities, and the management of voltage quality for photovoltaic power stations becomes a key cha...

Recently, deep learning has yielded transformative success across optics and photonics, especially in optical metrology. Deep neural networks (DNNs) with a fully convolutional architecture (e.g., U-Net and its derivative...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

ObjectiveCurrently, the insufficient full-element digitization and the prevalence of “data silos” in fully mechanized mining faces (FMMF) result in poor cutting precision and operational instability of shearers under...

Background/Aim: Age estimation is of great importance due to legal requirements. Although there are many methods used, most of them are based on age related dental changes. Artificial intelligence based programs, one of ...

The huge rise in the number of medical images has caused a major problem in radiology departments. Radiologists are now working harder than ever, which affects the quality of their diagnoses and patient care. It takes 15...

The perception systems for Traffic Sign Recognition (TSR) and Lane Line Recognition (LLR) are foundational pillars for the safe and effective operation of Advanced Driver-Assistance Systems (ADAS) and fully autonomous ve...

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with...

We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 e...

We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - Gradient-weighted Class Activat...

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, expo...

Importance: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules ...