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Using an Inspired Quantum-Classical Sequential Neural Network to Segment Liver Tumor Images Accurately

Sonwane Suchitra Shivaji Rao, K. Gangadhara Rao • Journal of Applied Science and Engineering (2026)

Medical analytics based on multimodal intelligence are essential to contemporary healthcare, especially in the diagnosis and detection of liver cancer. However, low contrast, varied textures, and irregular tumor forms in medical imaging con...

DOAJ Open Access (DOAJ) DOI: 10.6180/jase.202701_36.052

Slimmable Neural Networks

Jiahui Yu, Linjie Yang, Ning Xu, Yang, Jianchao et al. • arXiv (Cornell University) (2018)

We present a simple and general method to train a single neural network executable at different widths (number of channels in a layer), permitting instant and adaptive accuracy-efficiency trade-offs at runtime. Instead of training individua...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1812.08928

Self-Normalizing Neural Networks

Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter • arXiv (Cornell University) (2017)

Deep Learning has revolutionized vision via convolutional neural networks (CNNs) and natural language processing via recurrent neural networks (RNNs). However, success stories of Deep Learning with standard feed-forward neural networks (FNN...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1706.02515

Nonresonant renormalization scheme for twist-2 operators in SU(N) Yang–Mills theory

Francesco Scardino • European Physical Journal C: Particles and Fields (2024)

Abstract Recently, the short-distance asymptotics of the generating functional of n-point correlators of twist-2 operators in SU(N) Yang–Mills (YM) theory has been worked out in Bochicchio et al. (Phys Rev D 108:054023, 2023). The above com...

DOAJ Open Access (DOAJ) DOI: 10.1140/epjc/s10052-024-13590-z

A Multi-Stage NLP Framework for Knowledge Discovery from Crop Disease Research Literature

Jantima Polpinij, Manasawee Kaenampornpan, Christopher S. G. Khoo, Wei-Ning Cheng et al. • Mathematics (2026)

Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...

DOAJ Open Access (DOAJ) DOI: 10.3390/math14020299

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Vinodkumar Patil, Manisha Patil, Smital Patil, Satish Desale • Advances in Engineering and Intelligence Systems (2026)

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

DOAJ Open Access (DOAJ) DOI: 10.22034/aeis.2026.570662.1424

A review of convolutional neural networks in computer vision

Xia Zhao, Limin Wang, Yufei Zhang, Xuming Han et al. • Artificial Intelligence Review (2024)

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of dee...

OPENALEX cc-by DOI: https://doi.org/10.1007/s10462-024-10721-6

On Calibration of Modern Neural Networks

Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger • arXiv (Cornell University) (2017)

Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applications. We discover that modern neural networks, unlike thos...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1706.04599

Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training.

Francisco J Zamora-Martínez, Salvador España-Boquera, Maria Jose Castro-Bleda, Adrian Palacios-Corella • PLoS ONE (2018)

This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input contexts of different le...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0200884

A Selective Overview of Deep Learning

Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science (2021)

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...

OPENALEX Open Access DOI: https://doi.org/10.1214/20-sts783 PMC: 8300482

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences (2024)

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrras.2024.101172

Machine learning insight in quality control and maintenance management of drilling mud pumps

Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data (2026)

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

DOAJ Open Access (DOAJ) DOI: 10.1186/s40537-026-01475-9

A Proposed Arabic Handwritten Text Normalization Method

Tarik Abu-Ain, Siti Norul Huda Sheikh Abdullah, Khairuddin Omar, Ashraf Abu-Ein et al. • Journal of ICT Research and Applications (2014)

Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, t...

DOAJ Open Access (DOAJ) DOI: 10.5614/itbj.ict.res.appl.2013.7.2.5

Detection and Classification of Abnormities of First Heart Sound Using Empirical Wavelet Transform

Haixia Li, Yongfeng Ren, Guojun Zhang, Renxin Wang et al. • IEEE Access (2019)

It is expected that an automatic detection and classification algorithm for the abnormities of first heart sound (S1) can realize computer artificial intelligence diagnosis of some relative cardiovascular disease. Few studies have focused o...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2943705

Personalized ideological content recommendation via reinforcement learning as a digital therapeutic for anxiety reduction in youth

Yu Wang • Discover Artificial Intelligence (2026)

Abstract Adaptive digital therapies are needed with increasing rates of youth anxiety. However, existing systems lack personalization and dynamic learning. To solve this, the proposed research is to build a personalized ideological content ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01840-w