paulpanwang/interview

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paulpanwang/interview

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机器学习岗位常见面试题整理

Underwater-Image-De-Scattering

De-scattering and edge enhancing are critical procedures for underwater images which surfer from serious detail loss, color deviation and blurring. In this work, a novel method has been proposed to enhance contrast and edge of underwater images.

Face_alignment

In face-related applications, the obtained face images often have different shapes. At this time, the face shape needs to be normalized. Face alignment is the process of normalizing two different shapes, placing one shape as close to the other as possible.

YOLO-Android

Age_and_Gender_Predict

A person's face provides a lot of information such as age, gender and identity. Faces plays an important role in the estimation/prediction of the age and gender of persons, just by looking at their face.

Jupyter Notebook

Gen6DNeRF

SPECK

SPECK——a lossless compression method for 3-D color images is proposed. First，the IIntKLT is applied to reduce the redundancies between the color components，so that the complete reversible transform is guaranteed，and then by using SPECK，the performance of coding is improved． The results of experimentation of standard testing color image，show that the new approach has an increase of 0. 1 bpp in lossless image compression，and in the case of complete reversible lossy compression，compared with JPEG2000，it at most has a increase of 0. 88 dB．

GLCM

GLCM calculates the statistics specified in properties from the gray-level co-occurrence matrix glcm. glcm is an m-by-n-by-p array of valid gray-level co-occurrence matrices. If glcm is an array of GLCMs, stats is an array of statistics for each glcm. graycoprops normalizes the gray-level co-occurrence matrix (GLCM) so that the sum of its elements is equal to 1. Each element (r,c) in the normalized GLCM is the joint probability occurrence of pixel pairs with a defined spatial relationship having gray level values r and c in the image. graycoprops uses the normalized GLCM to calculate properties.