Representasi kekerasan terhadap perempuan dalam film "The Photograph"

Film "The Photograph" adalah sebuah film yang menceritakan tentang kehidupan perempuan yang mengalami tindak kekerasan, baik secara fisik maupun non fisik. Kekerasan tersebut dilakukan oleh kedua tokoh laki-laki. Dengan menggunakan metode analisis isi kualitatif, hasil penelitian ini menunjukkan bahwa bentuk-bentuk kekerasan terhadap perempuan dapat berupa kekerasan fisik, seksual dan psikis. Ketiga bentuk kekerasan tersebut yang dialami oleh tokoh utama dan tokoh pendamping perempuan

Landvorme en sandverplasing oor die Kuisebdelta

Proefskrif (M. Sc.) -- Universiteit van Stellenbosch, 1990.Full text to be digitised and attached to bibliographic record

Een atjineesche vlag met arabische opschriften /

"Overgenomen uit het Tijdschrift voor Nederlandsch Indië, November 1873 [p. 325-840]".Mode of access: Internet

Disputatio medica inauguralis de chlōrōsei sive morbo virgineo : qvam divino favente numine ex authoritate Magnifici D. Rectoris, D. Abrahami Heydani, SS. Theol. Doct. ... pro gradu doctoratus, & summis in medicina privilegiis consequendis, publico examini subjicit Theodorus Maton, Lugduno-Batav., ad diem 12. Octobris, horis locoque solitis.

Mode of access: Internet.Photocopy

METROTRANS: A CROWD-SOURCED PUBLIC TRANSPORTATION APPLICATION IN JAKARTA ON ANDROID PLATFORM FOR PT LINTAS KARYA INTEGRASI

METROTRANS: A CROWD-SOURCED PUBLIC TRANSPORTATION APPLICATION IN JAKARTA ON ANDROID PLATFORM FOR PT LINTAS KARYA INTEGRASI

Evaluating CNN interpretability on sketch classification

While deep neural networks (DNNs) have been shown to outperform humans on many vision tasks, their intransparent decision making process inhibits wide-spread uptake, especially in high-risk scenarios. The BagNet architecture was designed to learn visual features that are easier to explain than the feature representation of other convolutional neural networks (CNNs). Previous experiments with BagNet were focused on natural images providing rich texture and color information. In this paper, we investigate the performance and interpretability of BagNet on a data set of human sketches, i.e., a data set with limited color and no texture information. We also introduce a heatmap interpretability score (HI score) to quantify model interpretability and present a user study to examine BagNet interpretability from user perspective. Our results show that BagNet is by far the most interpretable CNN architecture in our experiment setup based on the HI score