An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in …
With artificial intelligence permeating conversations and marketing interactions through
digital technologies and media, machine learning models, in particular, natural language …
digital technologies and media, machine learning models, in particular, natural language …
Micronets: Neural network architectures for deploying tinyml applications on commodity microcontrollers
Executing machine learning workloads locally on resource constrained microcontrollers
(MCUs) promises to drastically expand the application space of IoT. However, so-called …
(MCUs) promises to drastically expand the application space of IoT. However, so-called …
Audio based depression detection using Convolutional Autoencoder
Depression is a serious and common psychological disorder that requires early diagnosis
and treatment. In severe episodes the condition may result in suicidal thoughts. Recently …
and treatment. In severe episodes the condition may result in suicidal thoughts. Recently …
[PDF][PDF] Ensemble Of Complementary Anomaly Detectors Under Domain Shifted Conditions.
We present our submission to the DCASE2021 Challenge Task 2, which aims to promote
research in anomalous sound detection. We found that blending the predictions of various …
research in anomalous sound detection. We found that blending the predictions of various …
Tinyvers: A tiny versatile system-on-chip with state-retentive eMRAM for ML inference at the extreme edge
Extreme edge devices or Internet-of-Things (IoT) nodes require both ultra-low power (ULP)
always-on (AON) processing as well as the ability to do on-demand sampling and …
always-on (AON) processing as well as the ability to do on-demand sampling and …
An anomalous sound detection methodology for predictive maintenance
In the last decade, Anomalous Sound Detection (ASD) is becoming an increasingly
challenging task for a plethora of applications due to the widespread diffusion of Deep …
challenging task for a plethora of applications due to the widespread diffusion of Deep …
A novel unsupervised graph wavelet autoencoder for mechanical system fault detection
T Li, C Sun, R Yan, X Chen - Journal of Intelligent Manufacturing, 2024 - Springer
Reliable fault detection is an essential requirement for safe and efficient operation of
mechanical systems in various industrial applications. As machine complexity increases, the …
mechanical systems in various industrial applications. As machine complexity increases, the …
A dual architecture fusion and AutoEncoder for automatic morphological classification of human sperm
Infertility has become a common problem in global health, and unsurprisingly, many couples
need medical assistance to achieve reproduction. Many human behaviors can lead to …
need medical assistance to achieve reproduction. Many human behaviors can lead to …
Predictive evaluation of spectrogram-based vehicle sound quality via data augmentation and explainable artificial Intelligence: Image color adjustment with brightness …
D Kim, J Lee - Mechanical Systems and Signal Processing, 2022 - Elsevier
In this study, a novel method for selecting the optimal data augmentation method in
combination with explainable artificial intelligence techniques is presented. Accordingly, a …
combination with explainable artificial intelligence techniques is presented. Accordingly, a …
Multi-label extreme learning machine (MLELMs) for bangla regional speech recognition
Extensive research has been conducted in the past to determine age, gender, and words
spoken in Bangla speech, but no work has been conducted to identify the regional language …
spoken in Bangla speech, but no work has been conducted to identify the regional language …