Abstract: A memory array and an operation method of the memory array are provided. The memory array includes first and second ferroelectric memory devices formed along a gate electrode, a channel layer and a ferroelectric layer between the gate electrode and the channel layer. The ferroelectric memory devices include: a common source/drain electrode and two respective source/drain electrodes, separately in contact with a side of the channel layer opposite to the ferroelectric layer, wherein the common source/drain electrode is disposed between the respective source/drain electrodes; and first and second auxiliary gates, capacitively coupled to the channel layer, wherein the first auxiliary gate is located between the common source/drain electrode and one of the respective source/drain electrodes, and the second auxiliary gate is located between the common source/drain electrode and the other respective source/drain electrode.

Abstract: An optoelectronic package and a method for producing the optoelectronic package are provided. The optoelectronic package includes a carrier, a photonic device, a first encapsulant and a second encapsulant. The photonic device is disposed on the carrier. The first encapsulant covers the carrier and is disposed around the photonic device. The second encapsulant covers the first encapsulant and the photonic device. The first encapsulant has a topmost position and a bottommost position, and the topmost position is not higher than a surface of the photonic device.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.

Abstract: In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.