GIT: A Transformer-Based Deep Learning Model for Geoacoustic Inversion

Deep learning-based CAD systems for mammography: A review article

Breast cancer is one of the most common types of cancer in women. Screening mammography is a low‑dose X‑ray examination of breasts, which is conducted to detect breast cancer at early stages when the cancerous tumor is too small to be felt as a lump. Screening mammography is conducted for women with no symptoms of breast cancer, for early detection of cancer when the cancer is most treatable an...

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Neural Direct Approaches for Geoacoustic Inversion

Broadband synthetic aperture geoacoustic inversion.

A typical geoacoustic inversion procedure involves powerful source transmissions received on a large-aperture receiver array. A more practical approach is to use a single moving source and/or receiver in a low signal to noise ratio (SNR) setting. This paper uses single-receiver, broadband, frequency coherent matched-field inversion and exploits coherently repeated transmissions to improve estim...

Low Frequency Geoacoustic Inversion Method

APPROACH Consider the simulated SW06 scenario with a “true” bottom consisting of 3 sediment layers (to­ taling 22m in depth extent – a medium thickness) where all three sediment layers are each defined by a linear sound-speed profile (and constant densities) all over a half-space (constant sound-speed and density) as seen in Fig. 1. For the inversion processing we shall (as in earlier work) ass...