From Tables 1 and 2, the stacking module used in ML-YOLOv3 reduces parameter sizes and FLOPs by 93.59% compared with YOLOv3. This is mainly because only 1/2 of the channels are involved in the convolution. In addition, the traditional 3 \(\times\) 3 convolution is abandoned, and depthw...
The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information. Type: Array of strings Array Members: Minimum number of 1 item. Maximum num...
We consider the classical ML models previously described, utilizing a random Fourier feature map62. While the indicator function feature map was a useful tool to obtain our rigorous guarantees, random Fourier features are more robust and commonly used in practice. Moreover, we still expect our ...
The following example shows how this"scale"value is used to rescale theencoded_labelvalues of the input annotation image when they are mapped to themapped_labelvalues to be used in training. The label values in the input annotation image are 0, 3, 6, with scale 3, so they are mapped to...
A machine learning algorithm is a set of rules or processes used by an AI system to conduct tasks.
The Hungarian Algorithm is a method used in computer science to match the output of a model with ground truth by finding the optimal assignment between two sets of elements. AI generated definition based on: Engineering Applications of Artificial Intelligence, 2023 ...
In total, 1011 myopic children aged 6 to 18 years participated in this study. Cross-sectional datasets were used to optimize the ML algorithms. The input variables included age, sex, central corneal thickness (CCT), spherical equivalent refractive error (SER), mean K reading (K-mean), and...
ML-based solutions that address the predictability of drone mobility are likely to be more prominent in future. In [33], the Q-learning algorithm was used to learn the optimum bias value of each BS according to the loads of static BSs. In [34], the number of future users within cells ...
Although reinforcement learning (RL) has proven to be a successful paradigm for training AI models in navigation tasks, often used in gaming, existing RL methods are not yet robust enough to handle exogenous noise. While they may be able to heuristically solve certain problems, such ...
the decoding complexity can be further reduced by comparing the path metric of ML tail-biting path with the threshold used in the bidirectional searching algorithm.Combing the Viterbi algorithm and bidirectional searching algorithm,a new ML decoding algorithm for tail-biting codes,which can be ...