After falling sick at the start of the month, I became more interested in exploring how the immune system and trauma release interact. I deeply suspected that there was a very significant link between...
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python) (⭐ 1402)
Fairness in deep learning models trained with high-dimensional inputs and subjective labels remains a complex and understudied area. Facial emotion recognition, a domain where datasets are often racially imbalanced, can lead to models that yield disp...
Large-scale models pre-trained on large-scale datasets have profoundly advanced the development of deep learning. However, the state-of-the-art models for medical image segmentation are still small-scale, with their parameters only in the tens of mil...
Studies on benign overfitting provide insights for the success of overparameterized deep learning models. In this work, we examine whether overfitting is truly benign in real-world classification tasks. We start with the observation that a ResNet mod...
A central challenge in quantum machine learning is the design and training of parameterized quantum circuits (PQCs). Much like in deep learning, vanishing gradients pose significant obstacles to the trainability of PQCs, arising from various sources....
After Chikn fought through the apartments he took the elevator down to the Deeper Apartments.. What he come across next almost made him pissed his pants.. Will Chikn defeat the terrifying looking cha...
Feb 18, 2026 · Employee safety is a top priority at Newell Brands. Over the past year, we maintained the programs that have allowed us to achieve a world-class safety record while deepening our training …
Segmentation of structural parts of 3D models of plants is an important step for plant phenotyping, especially for monitoring architectural and morphological traits. Current state-of-the art approaches rely on hand-crafted 3D local features for model...
Reliable and automated 3D plant shoot segmentation is a core prerequisite for the extraction of plant phenotypic traits at the organ level. Combining deep learning and point clouds can provide effective ways to address the challenge. However, fully s...
My tubes are tied, we've been married for almost 5 years. He works for a large gas station chain, and although I found them deep in his dashboard he tries to gaslight me by telling me these are sample...
May 30, 2025 · The word "sister" primarily refers to a female sibling but carries deeper meanings in cultural, emotional, and religious contexts. It is a word rich with emotional significance, symbolizing …
We present a new family of deep neural network-based dynamic systems. The presented dynamics are globally stable and can be conditioned with an arbitrary context state. We show how these dynamics can be used as structured robot policies. Global stabi...
An interesting example of the deep interrelation between Physics and Mathematics is obtained when trying to impose mathematical boundary conditions on physical quantum fields. This procedure has recently been re-examined with care. Comments on that...
Hughes designs, deploys, and operates secure, resilient networks that adapt as connectivity requirements evolve. Backed by deep expertise and proactive management, Hughes partners with …
In this article, we present the BTransformer18 model, a deep learning architecture designed for multi-label relation extraction in French texts. Our approach combines the contextual representation capabilities of pre-trained language models from the...
Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection. (⭐ 88)
Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection, semi-supervised anomaly detection (⭐ 153)
Reinforcement Learning (RL) can model complex behavior policies for goal-directed sequential decision making tasks. A hallmark of RL algorithms is Temporal Difference (TD) learning: value function for the current state is moved towards a bootstrapped...
We use galaxies detected in a deep ultraviolet XMM-Newton Optical Monitor image and a model that predicts UV galaxy counts based on local counts and evolution parameters to constrain galaxy evolution to Z=1.2. The 17' square 2000 angstrom (UVW2 fil...