A few years back, when the image processing hardware and software were created, it was limited, and most of the time, object detection would fail., But as with time, the advancement in technology has significantly changed the scenario. A lot of researchers worked in this field to carry out a solution through which they can detect objects in any field, especially in the robotic domain [1]. In today's world, with so much research in the field of deep learning, it is very easy to identify and detect any object using computer vision. This paper focuses on the various deep learning technologies and algorithms through which object detection can be done. A new and advanced deep learning technology known as salient object detection has been discussed. Also, the 3D object detection and the end-to-end approach for object detection are discussed. The existing methods of deep learning through which object detection can be done. The applications in which object detection is being used and the importance of object detection. It also reports; what the predecessors have done, what problems have been solved by them, how they solved these problems, the characteristics of the predecessors' methods and their future work.

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The low-temperature sintering of (Bi 0.5 Na 0.5 )TiO 3 -based ceramics can be achieved by sintering aid CuO. Piezoelectric ceramics (1 − x)[0.90-(Bi 0.5 Na 0.5 )TiO 3 − 0.10SrTiO 3 ] − xCuO (BNT-ST-Cu) with x = 0, 0.01, 0.02, 0.03, and 0.04 were prepared through the mixed oxide route. A tetragonal structure was indexed for the undoped sample. Its structure was found to be changed to a pseudocubic when Cu was added. For undoped Cu samples, the sintering temperature (T s ) for sufficient densification was 1160 °C. However, T s was reduced to 1090−1120 °C for Cu-added specimens. Field emission scanning electron microscopy (FE-SEM) showed a uniform and dense grain morphology for all samples. The maximum dielectric constant temperature (T m ) was decreased with the doping concentration of Cu and applied frequency. The strain was increased with Cu concentration and had the maximum value of 500 pm/V for the sample x = 0.02 with symmetric and slim strain loops.

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